Computer-assisted biology: Decoding noisy data to predict cell growth

Researchers from The University of Tokyo Institute of Industrial Science used artificial intelligence to obtain a more objective understanding of cell growth and division without preconceived assumptions. Using a deep-learning neural network, they were able to more accurately model the complex processes that affect cell size over time. This work may lead to advances in microbiology and industrial production of microorganisms.